• IEIE Transactions on Smart Processing and Computing
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• v.4 no.6
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• pp.413-421
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• 2015

Regularized Blind Deconvolution is a problem applicable in degraded images in order to bring the original image out of blur. Multichannel blind Deconvolution considered as an optimization problem. Each step in the optimization is considered as variable splitting problem using an algorithm called Alternating Minimization Algorithm. Each Step in the Variable splitting undergoes Augmented Lagrangian method (ALM) / Bregman Iterative method. Regularization is used where an ill posed problem converted into a well posed problem. Two well known regularizers are Tikhonov class and Total Variation (TV) / L2 model. TV can be isotropic and anisotropic, where isotropic for L2 norm and anisotropic for L1 norm. Based on many probabilistic model and Fourier Transforms Image deblurring can be solved. Here in this paper to improve the performance, we have used an adaptive regularization filtering and isotropic TV model Lp norm. Image deblurring is applicable in the areas such as medical image sensing, astrophotography, traffic signal monitoring, remote sensors, case investigation and even images that are taken using a digital camera / mobile cameras.

• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.261-267
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• 2007

The research about Intelligence Transport Systems(ITS) is actively studied for the traffic problem solution recently. Also, the various methods to detect vehicles moving in the roads are studied. This research using image processing technology is to give the drivers the road information quickly by developing Vehicle Detection System that detects through traffics. Purpose or this research is developing efficient algorithm to facilitate hardware composition. We use morphology method to extract corner points in the images captured by CCD camera. Also, the proposed algorithm detects vehicle's moving area by using motion vectors between corner points. The experiments of the proposed algorithm whose processing time was shortened show good results in vehicle detection on the live road images.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.3
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• pp.239-242
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• 2015

In this paper, we propose a walking assisting system for blind people using Android smartphone and Arduino board. In our proposed system, we use an Android smartphone case and an external ultrasonic sensor to detect the obstacles ahead. In this manner, blind people is able to aware unexpected objects by smartphone speakers or vibration functionality. In addition, the walking assisting system is also designed a notice system which will be triggered by built-in smartphone camera flash when blind people walk in some darkness place. The experimental results from real experiments on blind people have demonstrated the applicability of our walking assisting system, when it not only efficiently helps blind people avoid obstacles ahead but also possible traffic collisions in darkness condition.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.5
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• pp.1141-1147
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• 2017

An unmanned aerial vehicle(UAV), commonly known as a drone, is an aircraft without a human pilot aboard, which is operated by wireless device. A drone provides the capability for the aerial search and traffic control as a police equipment. It has benefits for the missions for the aerial photography with the high resolution camera which can replace eye-dependent search processes. Moreover it has advantage of retrieving several times for the recorded videos. However, if the law enforcement agency misuse and overuse a drone for investigations and search missions without certain regulations and principles, it breaches privacy and personal information infringement. In this paper, we issue a lawful challenges on drone operations and discuss solutions to those challenges.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.241-244
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• 2009

Recently car navigation systems which are widely spreaded and provide routes exactly have been evolved. The systems use various information and techniques as follows. In order to provide shortest path with good flow, realtime traffic information provided by DMB is used. Augmented reality technique is also introduced to give the sense of real to driver by displaying real images captured by camera during driving. But these operate well when the GPS receives data normally. Exact information about the position of vehicles becomes a base that supports the above function with realities. This paper proposes a method for compensating a given path. It uses various information by integrated vehicle networks when the GPS does not operates normally.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.1-20
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• 2022

As unmanned aerial vehicle (UAV) technology grew in popularity over the years, it was introduced for air quality monitoring. This can easily be used to estimate the sidewalk emission concentration by calculating road traffic emission factors of different vehicle types. These calculations require a simulation of the spread of pollutants from one or more sources given for estimation. For this purpose, a Gaussian plume dispersion model was developed based on the US EPA Motor Vehicle Emissions Simulator (MOVES), which provides an accurate estimate of fuel consumption and pollutant emissions from vehicles under a wide range of user-defined conditions. This paper describes a methodology for estimating emission concentration on the sidewalk emitted by different types of vehicles. This line source considers vehicle parameters, wind speed and direction, and pollutant concentration using a UAV equipped with a monocular camera. All were sampled over an hourly interval. In this article, the YOLOv5 deep learning model is developed, vehicle tracking is used through Deep SORT (Simple Online and Realtime Tracking), vehicle localization using a homography transformation matrix to locate each vehicle and calculate the parameters of speed and acceleration, and ultimately a Gaussian plume dispersion model was developed to estimate the CO, NOx concentrations at a sidewalk point. The results demonstrate that these estimated pollutants values are good to give a fast and reasonable indication for any near road receptor point using a cheap UAV without installing air monitoring stations along the road.

• The KIPS Transactions:PartB
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• v.18B no.5
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• pp.255-264
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• 2011

In this paper, we propose a forward vehicle detection algorithm using column detection and bird's-eye view mapping based on stereo vision. The algorithm can detect forward vehicles robustly in real complex traffic situations. The algorithm consists of the three steps, namely road feature-based column detection, bird's-eye view mapping-based obstacle segmentation, obstacle area remerging and vehicle verification. First, we extract a road feature using maximum frequent values in v-disparity map. And we perform a column detection using the road feature as a new criterion. The road feature is more appropriate criterion than the median value because it is not affected by a road traffic situation, for example the changing of obstacle size or the number of obstacles. But there are still multiple obstacles in the obstacle areas. Thus, we perform a bird's-eye view mapping-based obstacle segmentation to divide obstacle accurately. We can segment obstacle easily because a bird's-eye view mapping can represent the position of obstacle on planar plane using depth map and camera information. Additionally, we perform obstacle area remerging processing because a segmented obstacle area may be same obstacle. Finally, we verify the obstacles whether those are vehicles or not using a depth map and gray image. We conduct experiments to prove the vehicle detection performance by applying our algorithm to real complex traffic situations.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.9 s.351
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• pp.120-127
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• 2006

In Korea the vehicle enforcement system(VES) detects speeding vehicle using two inductive loop detectors. And the speed reliability of theirs are evaluated through the analysis of image frame which is captured from video camera. This method is validated to evaluate VES on Korea Laboratory Accreditation Scheme(KOLAS) but it needs much time and expense for the analysis of image frame. Because the number of VES are increasing rapidly, the requirement of new evaluation method is necessary. On this paper, the tape switch sensor as a substitution of existing method was introduced and its application on the site are discussed. On the site test we compared the tape switch sensor on the speed measurement of vehicle with the video image frame. As a result we have founded that the tape switch sensor is evaluated to be feasible system on site in respect to measure the overspeed vehicle.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.1
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• pp.97-104
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• 2016

In Korea, the number of crash accident victims per 100,000 population is three times higher than the average of OECD. In particular, 60% of it occurs on the community road. Thus, this study intends to analyze the causes of such accidents through a pedestrian and vehicle traffic survey. The purpose is to establish practical safety enhancement measures for community roads. In recent years, lots of changes have occurred in the pedestrian environment. A traffic survey shows that 65% of pedestrians walk on the right and 17% of people use smart-phones while walking. An eye camera experiment shows that the operation load of drivers on the community roads is more than 4 times higher than those in urban roads. According to a speed survey, 62% of vehicles drive at 30km/h or above. The characteristics of accidents on community roads are as follows. First, the ratio of accidents on the edge of the road is 2.3 times as high as those on other roads. Second, when people walk on the right, the ratio of accidents is 2.5 times as high as that of walking on the left. Third, it becomes more dangerous when people cross the road from the right to the left. The majority of accidents is caused by unsafe driving (84.4%). When a vehicle makes a left turn, the likelihood of accidents is 2.3 times as high as those caused by a right turn. The ratio of accidents caused by vehicles going backwards is 14% among all accidents. In community roads, the focus of drivers should be at least 4 times higher than those on urban roads. Thus, walking in the opposite direction of vehicles and careless behaviors are highly likely lead to accidents.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.1
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• pp.1-15
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• 2011

The RLC systems is one of the intelligent transportation systems that has gained a nation-wide support for last decades and being installed to discourage motorists from running the red lights at signalized intersections. It is taken for granted that the RLC will provide motorists with increased safety, so that their installments are always justifiable. However, in order to acquire more efficiency and wider supports from the general public in future RLC installments, an improved methodology for analyzing the effects of the RLC systems is required. In order to satisfy this requirement, this research performed the following tasks. First, the number of signal violations after the RLC systems were investigated in order to check its resulting effects. Second, the number of crashes after the RLC systems were collected and compared with the number of signal violations. Third, a statistical analysis was carried out to develop the relationships between the signal violations and the crashes based on negative binomial distribution. The analysis revealed that the number of crashes has a close relationship with the RLC placement, traffic volume, vehicle speed, the number of phases, and the number of lanes for major approaches. Finally, based on the results found in this analysis, this research presents a methodology for analyzing the safety effects of placing the RLC that should be of service when investigating the economic consequences of the RLC systems.